http://2009.igem.org/wiki/index.php?title=Special:Contributions/LUIS_DE_JESUS&feed=atom&limit=50&target=LUIS_DE_JESUS&year=&month=2009.igem.org - User contributions [en]2024-03-29T07:31:09ZFrom 2009.igem.orgMediaWiki 1.16.5http://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-12-09T06:54:48Z<p>LUIS DE JESUS: </p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
[[Image:Zebra.jpg|thumb|200px|zebra stripes pattern]]<br />
[[Image:Leopard.jpg|thumb|200px|leopard spots pattern]]<br />
<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & long range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
There are some variants of the classical Activator-Inhibitor system, like the Activator-Inhibitor with Substrates. Those systems describe the aditional existence of a substance that is degraded or inactivated along the time and the production of the activator is limited to its availability. This kind of substrates can sometimes play the role of the inhibitor, and due to this duality we can model our project in several ways with no loss of generality.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and long range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
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The Synthetic Biology has became in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could behave as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradients of morphogens in the media and have the potential to accordingly differentially respond. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfills the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book literaly says : <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
<br />
an advise that few teams in the past years' competitions may have considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Meinhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that genes of the quorum system ''las'' will have the role of the Activator, while genes of the ''lux'' quorum system are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'', ''Las'' and ''AI'', ''PAI'' lactones respectively. This compounds are very small and travel through the membrane rapidly diffusing in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''. in our genetic network the cell will differentially respond to the different concentrations in the gradients of ''PAI'' and ''AI'' by expressing different levels of ''GFP''.<br />
<br />
<br />
We also used a constitutive ''Lac'' inverter that allows us to control the production of ''LasR'' with ''IPTG'' and a constitutive ''Tet'' inverter that allows us to control ''LuxR'' with ''aTc. ''The controlling system of inverters provide a good way to make more sensitive the parameters adjustment.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
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The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
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<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
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This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
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<br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to be controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the BioBricks system works?, in this subsection we will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its controlling promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, and if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Long range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
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==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
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The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Synthesizing===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because it recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farther place the inhibitory morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T03:20:04Z<p>LUIS DE JESUS: /* 50pxPlasmids */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
These two biobricks are the main Activator-Inhibitor system, as showned below they are in two different plasmids, and the idea is transform Top10 cells with them in petri dishes with IPTG and ATC.<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
This biobricks are though like construction intermediates necessary to build the main and project biobricks.<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
<br />
Check registry for more info with the name of the biobrick<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Description<br />
! Image<br />
|-<br />
| SENT <br />
| BBa_K091146 & BBa_S03154 - >BBa_K266005 <br />
| [[Image:AI Biobricks.jpg|200px]]]<br />
|-<br />
| SENT<br />
| BBa_K266005 & BBa_E0840 - >BBa_K266006 <br />
| [[Image:AI Biobricks2.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_psb1c3 & BBa_K266006 - >BBa_K266006-Cm<br />
| [[Image:AI Biobricks3.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_K266006-Cm & BBa_K266000 - >BBa_K266007 <br />
| [[Image:AI Biobricks4.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_R0079 & BBa_F1610 - >BBa_K266000 <br />
| [[Image:AI Biobricks5.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_K116640 & BBa_K145201 - >BBa_K266001 <br />
| [[Image:AI Biobricks6.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_B0015 & BBa_C0079 - >BBa_K266002<br />
| [[Image:AI Biobricks7.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_K266002 & PCR AMPLICON - >BBa_K266003<br />
| [[Image:AI Biobricks8.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_J23100 & BBa_K266003 - >BBa_K266004<br />
| [[Image:AI Biobricks9.jpg|200px]]<br />
|-<br />
| PENDING <br />
| BBa_K266001 & BBa_K266004 - >BBa_K266011<br />
| [[Image:AI Biobricks10.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_J23100 & BBa_Q04121 - >BBa_K266008<br />
| [[Image:AI Biobricks11.jpg|200px]]<br />
|-<br />
| SENT<br />
| Ba_K266008 & BBa_B0034 - >BBa_K266009<br />
| [[Image:AI Biobricks12.jpg|200px]]<br />
|}<br />
<br />
==[[Image:Month-icon.png | 50px]]Results==<br />
{| style=" border="0"<br />
|- <br />
| [[Image:Control1.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 6,4x<br />
|-<br />
| [[Image:1601.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 6,4x<br />
|-<br />
|[[Image:Control2.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 19x<br />
|-<br />
| [[Image:1602.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 19x<br />
|-<br />
|}<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T03:18:38Z<p>LUIS DE JESUS: /* 50pxPlasmids */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
These two biobricks are the main Activator-Inhibitor system, as showned below they are in two different plasmids, and the idea is transform Top10 cells with them in petri dishes with IPTG and ATC.<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
This biobricks are though like construction intermediates necessary to build the main and project biobricks.<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
Check registry for more info with the name of the biobrick<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Description<br />
! Image<br />
|-<br />
| SENT <br />
| BBa_K091146 & BBa_S03154 - >BBa_K266005 <br />
| [[Image:AI Biobricks.jpg|200px]]]<br />
|-<br />
| SENT<br />
| BBa_K266005 & BBa_E0840 - >BBa_K266006 <br />
| [[Image:AI Biobricks2.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_psb1c3 & BBa_K266006 - >BBa_K266006-Cm<br />
| [[Image:AI Biobricks3.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_K266006-Cm & BBa_K266000 - >BBa_K266007 <br />
| [[Image:AI Biobricks4.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_R0079 & BBa_F1610 - >BBa_K266000 <br />
| [[Image:AI Biobricks5.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_K116640 & BBa_K145201 - >BBa_K266001 <br />
| [[Image:AI Biobricks6.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_B0015 & BBa_C0079 - >BBa_K266002<br />
| [[Image:AI Biobricks7.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_K266002 & PCR AMPLICON - >BBa_K266003<br />
| [[Image:AI Biobricks8.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_J23100 & BBa_K266003 - >BBa_K266004<br />
| [[Image:AI Biobricks9.jpg|200px]]<br />
|-<br />
| PENDING <br />
| BBa_K266001 & BBa_K266004 - >BBa_K266011<br />
| [[Image:AI Biobricks10.jpg|200px]]<br />
|-<br />
| SENT<br />
| BBa_J23100 & BBa_Q04121 - >BBa_K266008<br />
| [[Image:AI Biobricks11.jpg|200px]]<br />
|-<br />
| SENTB<br />
| Ba_K266008 & BBa_B0034 - >BBa_K266009<br />
| [[Image:AI Biobricks12.jpg|200px]]<br />
|}<br />
<br />
==[[Image:Month-icon.png | 50px]]Results==<br />
{| style=" border="0"<br />
|- <br />
| [[Image:Control1.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 6,4x<br />
|-<br />
| [[Image:1601.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 6,4x<br />
|-<br />
|[[Image:Control2.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 19x<br />
|-<br />
| [[Image:1602.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 19x<br />
|-<br />
|}<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T03:14:00Z<p>LUIS DE JESUS: /* 50pxPlasmids */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
These two biobricks are the main Activator-Inhibitor system, as showned below they are in two different plasmids, and the idea is transform Top10 cells with them in petri dishes with IPTG and ATC.<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
This biobricks are though like construction intermediates necessary to build the main and project biobricks.<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
Check registry for more info with the name of the biobrick<br />
BBa_K091146 & BBa_S03154 - >BBa_K266005 [[Image:AI Biobricks.jpg|200px]]]<br />
<br />
BBa_K266005 & BBa_E0840 - >BBa_K266006 [[Image:AI Biobricks2.jpg|200px]]<br />
<br />
BBa_psb1c3 & BBa_K266006 - >BBa_K266006 Cm[[Image:AI Biobricks3.jpg|200px]]<br />
<br />
BBa_K266006-Cm & BBa_K266000 - >BBa_K266007 [[Image:AI Biobricks4.jpg|200px]]<br />
<br />
<br />
BBa_R0079 & BBa_F1610 - >BBa_K266000 [[Image:AI Biobricks5.jpg|200px]]<br />
<br />
BBa_K116640 & BBa_K145201 - >BBa_K266001 [[Image:AI Biobricks6.jpg|200px]]<br />
<br />
BBa_B0015 & BBa_C0079 - >BBa_K266002[[Image:AI Biobricks7.jpg|200px]]<br />
<br />
BBa_K266002 & PCR AMPLICON - >BBa_K266003[[Image:AI Biobricks8.jpg|200px]]<br />
<br />
BBa_J23100 & BBa_K266003 - >BBa_K266004[[Image:AI Biobricks9.jpg|200px]]<br />
<br />
PENDING BBa_K266001 & BBa_K266004 - >BBa_K266011[[Image:AI Biobricks10.jpg|200px]]<br />
<br />
BBa_J23100 & BBa_Q04121 - >BBa_K266008[[Image:AI Biobricks11.jpg|200px]]<br />
<br />
BBa_K266008 & BBa_B0034 - >BBa_K266009[[Image:AI Biobricks12.jpg|200px]]<br />
<br />
==[[Image:Month-icon.png | 50px]]Results==<br />
{| style=" border="0"<br />
|- <br />
| [[Image:Control1.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 6,4x<br />
|-<br />
| [[Image:1601.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 6,4x<br />
|-<br />
|[[Image:Control2.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 19x<br />
|-<br />
| [[Image:1602.jpg | 250px|center]] || Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 19x<br />
|-<br />
|}<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T03:01:59Z<p>LUIS DE JESUS: /* 50pxPlasmids */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
These two biobricks are the main Activator-Inhibitor system, as showned below they are in two different plasmids, and the idea is transform Top10 cells with them in petri dishes with IPTG and ATC.<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
This biobricks are though like construction intermediates necessary to build the main and project biobricks.<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
Check registry for more info with the name of the biobrick<br />
[[Image:AI Biobricks.jpg|200px]]]<br />
[[Image:AI Biobricks2.jpg|200px]]<br />
[[Image:AI Biobricks3.jpg|200px]]<br />
[[Image:AI Biobricks4.jpg|200px]]<br />
[[Image:AI Biobricks5.jpg|200px]]<br />
[[Image:AI Biobricks6.jpg|200px]]<br />
[[Image:AI Biobricks7.jpg|200px]]<br />
[[Image:AI Biobricks8.jpg|200px]]<br />
[[Image:AI Biobricks9.jpg|200px]]<br />
[[Image:AI Biobricks10.jpg|200px]]<br />
[[Image:AI Biobricks11.jpg|200px]]<br />
[[Image:AI Biobricks12.jpg|200px]]<br />
<br />
==[[Image:Month-icon.png | 50px]]Results==<br />
<br />
[[Image:Control1.jpg | 350px|center]]<br />
<br />
Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 6,4x<br />
<br />
[[Image:1601.jpg | 350px|center]]<br />
<br />
Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 6,4x<br />
<br />
[[Image:Control2.jpg | 350px|center]]<br />
<br />
Regulatory LacI module coupled to the activator module with GFP reporter module. Basal conditions. 19x<br />
<br />
[[Image:1602.jpg | 350px|center]]<br />
<br />
Regulatory LacI module coupled to the activator module with GFP reporter module. IPTG 160mM. 19x<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks12.jpgFile:AI Biobricks12.jpg2009-10-22T02:35:04Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks11.jpgFile:AI Biobricks11.jpg2009-10-22T02:34:49Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks10.jpgFile:AI Biobricks10.jpg2009-10-22T02:34:36Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks9.jpgFile:AI Biobricks9.jpg2009-10-22T02:34:25Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks8.jpgFile:AI Biobricks8.jpg2009-10-22T02:33:11Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks7.jpgFile:AI Biobricks7.jpg2009-10-22T02:32:55Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks6.jpgFile:AI Biobricks6.jpg2009-10-22T02:32:49Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks5.jpgFile:AI Biobricks5.jpg2009-10-22T02:32:14Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks4.jpgFile:AI Biobricks4.jpg2009-10-22T02:31:59Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks3.jpgFile:AI Biobricks3.jpg2009-10-22T02:31:41Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks2.jpgFile:AI Biobricks2.jpg2009-10-22T02:31:04Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:AI_Biobricks.jpgFile:AI Biobricks.jpg2009-10-22T02:30:25Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/TeamTeam:IPN-UNAM-Mexico/Team2009-10-22T02:12:39Z<p>LUIS DE JESUS: /* Students */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]] About Us==<br />
Our group is formed by students and instructors from The National Laboratory for Biodiversity (LANGEBIO in spanish) and the National Autonomous University of Mexico (UNAM). The team is formed by undergraduate students in diverse disciplines such as mathematics, physics, biomedical sciences, biothecnology and biology. We believe these diversity is essential for the enrichment of our project. The instructors and advisors are also from different knowledge fields such as mathematics, biology, systems biology and computer science. <br />
The work method of the team was as a workshop and we held reunions three times a week in the first months and then we entered an intensive laboratory work period in an all day basis. The project was mainly coordinated and done by the students. Is only with team work that we were able accomplish what we have done in the project.<br />
As an original student initiative we have done the first fieldwork in molecular biology from our university, in order to collect species with unusual molecular mechanisms. This with the purpose of isolating them, characterize them, and try to use them in future synthetic constructions (you could see some photos in the future part of the wiki).<br />
<br />
==[[Image:Month-icon.png | 50px]] About the project==<br />
<br />
The project was born at Facultad de Ciencias synthetic biologic group as a theoretical approach of morphogenesis. Some ideas were proposed and developed theoretically on previous igem competitions since 2006 (e.g. [http://parts.mit.edu/igem07/index.php/Mexico oscillators])<br />
<br />
For this year students designed a device based on a gene synthetic network based on the lux and las quorum sensing genes and IPTG and ATC quemicals The team develop a modeling and simulation in silico which gave crucial dates about the experimental viability. With people of the Langebio IPN- Cinvestav Irapuato lab we was able to complete the theoretic design an tune up the experimental job. <br />
<br />
The assembly of regulation network started at Facultad de Ciencias, UNAM. Later we moved to Langebio IPN-Cinvestav lab to work together. <br />
<br />
To now the experimental advance has given us some ideas of how we must corroborate the Turing's proposal of morphogenesis from 1952<br />
<br />
We can say that given the nature our team so multidisciplinary that include students, advisors from Facultad de Ciencias, IIMAS and CINVESTAV Irapuato the first synthetic biology Mexican project proposed since 2006 produced great results in the experimental and theoretical field.<br />
<br />
On this date the proyect is 95% advance. <br />
<br />
<br />
<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]] Team members==<br />
=== Instructors ===<br />
<br />
{| style=" border="0"<br />
|- <br />
| [[Image:PadillaLongoria.jpg|left|100px|Pablo Padilla Longoria]] || Pablo Padilla Longoria || Mathematics - Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), UNAM<br />
|-<br />
<br />
| || Fabiola Ramirez Corona || Molecular Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Arturo Becerra || Origin of Life - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:fhq.jpg|left|100px|Francisco Quiroz]] || Francisco Hernández Quiroz || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|}<br />
<br />
=== Students ===<br />
<br />
{|<br />
|-<br />
| [[Image:Luis_Mtz.jpg|100px|left|Luis Martínez]]|| '''[http://openwetware.org/wiki/User:Luis_De_Jesus_Martinez Luis de Jesús Martínez Lomeli]''' || Mathematics - Facultad de Ciencias, UNAM. As an undergraduate math student my main interest in synthetic biology is develop biological systems that could give a new perspective about mathematical models (e.g. our project). My main role in the team was design the synthetic genetic network of biobricks that fulfill Turing hypothesis to generate spatiotemporal patterns. Besides, coordinate the whole project, work in the implementation of the system at lab, assist in the development of the model and stablish the colaboration with the LCG-UNAM mexican team. Lot of work! =)<br />
|-<br />
| [[Image:Chucho.jpg|100px]] || Jesús Pérez Juárez || Biology - Facultad de Ciencias, UNAM. I’m Jesús I study fourth year biology I'm so intersting in live sciences I think is a great oportunity to interdisciplinary collaborations and new aplications, I've realy enjoied the work with pysics and mathematics this summer. <br />
|-<br />
| [[Image:Isui.JPG|100px|left|Daniel Isui]]|| Daniel Isui Aguilar Salvador || Biomedical Research, Instituto de Investigaciones Biomédicas, Proudly UNAM. I'm an undergrad student on Biomedical Research (whatever that is), and I'm interested in original ways to apply biology. Since I was absent during part of the development of the project my work consisted in some lab work, but mainly I focused on the development of the single cell model and the kinetics implied on it. As well as in synthesizing the project to upload it to the wiki.<br />
|-<br />
| [[Image:Gil-mx-18.jpg|100px]] || Gilberto Gomez Correa || Physics, Facultad de ciencias, UNAM. My interest in synthetic biology is in the posible applications and the extent of them to every area of human action in particular its integration with biodegradation research and with neuroscience. My role in the team was as a multitask member mainly doing laboratory work, modeling in paper and in the computer and helping with the coordination of the project.<br />
<br />
|- <br />
| [[Image:Jose1.jpg|100px]]|| José Martínez Lomeli || Physics - Facultad de Ciencias, UNAM. I joined te team because I can see that the synthetic biology is a wonderful place where physics theories can interact with biology perfectly and both can get enrich. My role in the team was assist in the modeling part and help in the lab doing some experiments.<br />
|-<br />
| [[Image:Cjdg.png|100px]]|| [http://openwetware.org/wiki/User:Cristian_Delgado Cristian J. Delgado G.] || Undergraduate Biology Student Faculty of Sciences UNAM. work in rare and strange fields for biology, bionanotecnology, biomimetics, biorobotics, biological based devices, bio art, and anything that can be with "BIO",i believe that we dont have to close our view just on one side and turn back again to nature.On night i turn into dj and producer and i enjoy city night life. I love gadgets :D and computers, what else could make weird sounds and music?<br />
|-<br />
| [[Image:Pancho.jpg|100px|left|Pancho]] || Francisco Javier Razo Hernández || Plants Biotechnology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
| [[Image:Iledelaf.JPG|100px|left]] || Ileana de la Fuente Colmenares || Biology - Facultad de Ciencias, UNAM. I'm interested in designing biofuel cells from modificated microorganisms with rare metabolisms in relation with biorremediaton procesess and their implementation in Mexico. My roll in the Turing proyect was as a helper. I reviewed references and bibliography for the bioparts design and their characterization. <br />
|-<br />
| || Alin Acuña Alonzo || Biology - Facultad de Ciencias, UNAM<br />
|- <br />
| || Román Alfonso Acosta Díaz || Biology - Facultad de Ciencias, UNAM<br />
|-<br />
|[[Image:Eniak.jpg||100px|left]] || Eniak Hernandez || Biology - Facultad de Ciencias, UNAM<br />
|}<br />
<br />
=== Advisors ===<br />
<br />
{|<br />
|Elias Samra-Hassan || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|[[Image:Dr. Alexander de Luna Fors.jpg|100px]] || Alexander de Luna Fors || Molecular Biology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
|}<br />
<br />
==Aknowledgments==<br />
To Enrique Ramirez Corona (muzikavanzada at hotmail.com) for his wonderfull desings :D<br />
<br />
<br />
<br />
<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]] Team moments ==<br />
<br />
[[Image:México_CINVESTAV_1.JPG|center|700px|thumb|Team at lab in Langebio Cinvestav. In order of apparence, Jesus Pérez, Francisco Razo, Gilberto Gomez, Alexander De Luna, Roman Alfonso, Luis Martínez]]<br />
<br />
<br />
[[Image:Equipo21Agos09MX.jpg|center|700px|thumb|Team at Faculty of Sciences UNAM]]<br />
<br />
<br />
===Powered by Mexican Patriotic Power[https://static.igem.org/mediawiki/2009/6/66/Mexico_rules.jpg .]===<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/TeamTeam:IPN-UNAM-Mexico/Team2009-10-22T02:06:51Z<p>LUIS DE JESUS: about us</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]] About Us==<br />
Our group is formed by students and instructors from The National Laboratory for Biodiversity (LANGEBIO in spanish) and the National Autonomous University of Mexico (UNAM). The team is formed by undergraduate students in diverse disciplines such as mathematics, physics, biomedical sciences, biothecnology and biology. We believe these diversity is essential for the enrichment of our project. The instructors and advisors are also from different knowledge fields such as mathematics, biology, systems biology and computer science. <br />
The work method of the team was as a workshop and we held reunions three times a week in the first months and then we entered an intensive laboratory work period in an all day basis. The project was mainly coordinated and done by the students. Is only with team work that we were able accomplish what we have done in the project.<br />
As an original student initiative we have done the first fieldwork in molecular biology from our university, in order to collect species with unusual molecular mechanisms. This with the purpose of isolating them, characterize them, and try to use them in future synthetic constructions (you could see some photos in the future part of the wiki).<br />
<br />
==[[Image:Month-icon.png | 50px]] About the project==<br />
<br />
The project was born at Facultad de Ciencias synthetic biologic group as a theoretical approach of morphogenesis. Some ideas were proposed and developed theoretically on previous igem competitions since 2006 (e.g. [http://parts.mit.edu/igem07/index.php/Mexico oscillators])<br />
<br />
For this year students designed a device based on a gene synthetic network based on the lux and las quorum sensing genes and IPTG and ATC quemicals The team develop a modeling and simulation in silico which gave crucial dates about the experimental viability. With people of the Langebio IPN- Cinvestav Irapuato lab we was able to complete the theoretic design an tune up the experimental job. <br />
<br />
The assembly of regulation network started at Facultad de Ciencias, UNAM. Later we moved to Langebio IPN-Cinvestav lab to work together. <br />
<br />
To now the experimental advance has given us some ideas of how we must corroborate the Turing's proposal of morphogenesis from 1952<br />
<br />
We can say that given the nature our team so multidisciplinary that include students, advisors from Facultad de Ciencias, IIMAS and CINVESTAV Irapuato the first synthetic biology Mexican project proposed since 2006 produced great results in the experimental and theoretical field.<br />
<br />
On this date the proyect is 95% advance. <br />
<br />
<br />
<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]] Team members==<br />
=== Instructors ===<br />
<br />
{| style=" border="0"<br />
|- <br />
| [[Image:PadillaLongoria.jpg|left|100px|Pablo Padilla Longoria]] || Pablo Padilla Longoria || Mathematics - Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), UNAM<br />
|-<br />
<br />
| || Fabiola Ramirez Corona || Molecular Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Arturo Becerra || Origin of Life - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:fhq.jpg|left|100px|Francisco Quiroz]] || Francisco Hernández Quiroz || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|}<br />
<br />
=== Students ===<br />
<br />
{|<br />
|-<br />
| [[Image:Luis_Mtz.jpg|100px|left|Luis Martínez]]|| '''[http://openwetware.org/wiki/User:Luis_De_Jesus_Martinez Luis de Jesús Martínez Lomeli]''' || Mathematics - Facultad de Ciencias, UNAM. As an undergraduate math student my main interest in synthetic biology is develop biological systems that could give a new perspective about mathematical models (e.g. our project). My main role in the team was design the synthetic genetic network of biobricks that fulfill Turing hypothesis to generate spatiotemporal patterns. Besides, coordinate the whole project, work in the implementation of the system at lab, assist in the development of the model and stablish the colaboration with the LCG-UNAM mexican team. Lot of work! =)<br />
|-<br />
| [[Image:Chucho.jpg|100px]] || Jesús Pérez Juárez || Biology - Facultad de Ciencias, UNAM. I’m Jesús I study fourth year biology I'm so intersting in live sciences I think is a great oportunity to interdisciplinary collaborations and new aplications, I've realy enjoied the work with pysics and mathematics this summer. <br />
|-<br />
| [[Image:Isui.JPG|100px|left|Daniel Isui]]|| Daniel Isui Aguilar Salvador || Biomedical Research, Instituto de Investigaciones Biomédicas, Proudly UNAM. I'm an undergrad student on Biomedical Research (whatever that is), and I'm interested in original ways to apply biology. Since I was absent during part of the development of the project my work consisted in some lab work, but mainly I focused on the development of the single cell model and the kinetics implied on it. As well as in synthesizing the project to upload it to the wiki.<br />
|-<br />
| [[Image:Gil-mx-18.jpg|100px]] || Gilberto Gomez Correa || Physics, Facultad de ciencias, UNAM. My interest in synthetic biology is in the posible applications and the extent of them to every area of human action in particular its integration with biodegradation research and with neuroscience. My role in the team was as a multitask member mainly doing laboratory work, modeling in paper and in the computer and helping with the coordination of the project.<br />
<br />
|- <br />
| [[Image:Jose1.jpg|100px]]|| José Martínez Lomeli || Physics - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:Cjdg.png|100px]]|| [http://openwetware.org/wiki/User:Cristian_Delgado Cristian J. Delgado G.] || Undergraduate Biology Student Faculty of Sciences UNAM. work in rare and strange fields for biology, bionanotecnology, biomimetics, biorobotics, biological based devices, bio art, and anything that can be with "BIO",i believe that we dont have to close our view just on one side and turn back again to nature.On night i turn into dj and producer and i enjoy city night life. I love gadgets :D and computers, what else could make weird sounds and music?<br />
|-<br />
| [[Image:Pancho.jpg|100px|left|Pancho]] || Francisco Javier Razo Hernández || Plants Biotechnology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
| [[Image:Iledelaf.JPG|100px|left]] || Ileana de la Fuente Colmenares || Biology - Facultad de Ciencias, UNAM. I'm interested in designing biofuel cells from modificated microorganisms with rare metabolisms in relation with biorremediaton procesess and their implementation in Mexico. My roll in the Turing proyect was as a helper. I reviewed references and bibliography for the bioparts design and their characterization. <br />
|-<br />
| || Alin Acuña Alonzo || Biology - Facultad de Ciencias, UNAM<br />
|- <br />
| || Román Alfonso Acosta Díaz || Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Eniak Hernandez || Biology - Facultad de Ciencias, UNAM<br />
|}<br />
<br />
<br />
=== Advisors ===<br />
<br />
{|<br />
|Elias Samra-Hassan || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|[[Image:Dr. Alexander de Luna Fors.jpg|100px]] || Alexander de Luna Fors || Molecular Biology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
|}<br />
<br />
==Aknowledgments==<br />
To Enrique Ramirez Corona (muzikavanzada at hotmail.com) for his wonderfull desings :D<br />
<br />
<br />
<br />
<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]] Team moments ==<br />
<br />
[[Image:México_CINVESTAV_1.JPG|center|700px|thumb|Team at lab in Langebio Cinvestav. In order of apparence, Jesus Pérez, Francisco Razo, Gilberto Gomez, Alexander De Luna, Roman Alfonso, Luis Martínez]]<br />
<br />
<br />
[[Image:Equipo21Agos09MX.jpg|center|700px|thumb|Team at Faculty of Sciences UNAM]]<br />
<br />
<br />
===Powered by Mexican Patriotic Power[https://static.igem.org/mediawiki/2009/6/66/Mexico_rules.jpg .]===<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T01:48:47Z<p>LUIS DE JESUS: /* Auxiliary biobricks */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
These two biobricks are the main Activator-Inhibitor system, as showned below they are in two different plasmids, and the idea is transform Top10 cells with them in petri dishes with IPTG and ATC.<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
This biobricks are though like construction intermediates necessary to build the main and project biobricks.<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T01:46:56Z<p>LUIS DE JESUS: /* Projects */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
These two biobricks are the main Activator-Inhibitor system, as showned below they are in two different plasmids, and the idea is transform Top10 cells with them in petri dishes with IPTG and ATC.<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/TeamTeam:IPN-UNAM-Mexico/Team2009-10-22T01:43:19Z<p>LUIS DE JESUS: </p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<h1>[[Image:Month-icon.png | 50px]] About us</h1><br />
<br />
The project was born at Facultad de Ciencias synthetic biologic group as a theoretical approach of morphogenesis. Some ideas were proposed and developed theoretically on previous igem competitions since 2006 (e.g. [http://parts.mit.edu/igem07/index.php/Mexico oscillators])<br />
<br />
For this year students designed a device based on a gene synthetic network based on the lux and las quorum sensing genes and IPTG and ATC quemicals The team develop a modeling and simulation in silico which gave crucial dates about the experimental viability. With people of the Langebio IPN- Cinvestav Irapuato lab we was able to complete the theoretic design an tune up the experimental job. <br />
<br />
The assembly of regulation network started at Facultad de Ciencias, UNAM. Later we moved to Langebio IPN-Cinvestav lab to work together. <br />
<br />
To now the experimental advance has given us some ideas of how we must corroborate the Turing's proposal of morphogenesis from 1952<br />
<br />
We can say that given the nature our team so multidisciplinary that include students, advisors from Facultad de Ciencias, IIMAS and CINVESTAV Irapuato the first synthetic biology Mexican project proposed since 2006 produced great results in the experimental and theoretical field.<br />
<br />
On this date the proyect is 90% advance. <br />
<br />
<br />
<br />
<br />
<br />
<h1>[[Image:Month-icon.png | 50px]] Team members</h1><br />
<h2> Instructors </h2><br />
<br />
{| style=" border="0"<br />
|- <br />
| [[Image:PadillaLongoria.jpg|left|100px|Pablo Padilla Longoria]] || Pablo Padilla Longoria || Mathematics - Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), UNAM<br />
|-<br />
<br />
| || Fabiola Ramirez Corona || Molecular Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Arturo Becerra || Origin of Life - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:fhq.jpg|left|100px|Francisco Quiroz]] || Francisco Hernández Quiroz || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|}<br />
<br />
<h2> Students </h2><br />
<br />
{|<br />
|-<br />
| [[Image:Luis_Mtz.jpg|100px|left|Luis Martínez]]|| '''[http://openwetware.org/wiki/User:Luis_De_Jesus_Martinez Luis de Jesús Martínez Lomeli]''' || Mathematics - Facultad de Ciencias, UNAM. As an undergraduate math student my main interest in synthetic biology is develop biological systems that could give a new perspective about mathematical models (e.g. our project). My main role in the team was design the synthetic genetic network of biobricks that fulfill Turing hypothesis to generate spatiotemporal patterns. Besides, coordinate the whole project, work in the implementation of the system at lab, assist in the development of the model and stablish the colaboration with the LCG-UNAM mexican team. Lot of work! =)<br />
|-<br />
| [[Image:Chucho.jpg|100px]] || Jesús Pérez Juárez || Biology - Facultad de Ciencias, UNAM. I’m Jesús I study fourth year biology I'm so intersting in live sciences I think is a great oportunity to interdisciplinary collaborations and new aplications, I've realy enjoied the work with pysics and mathematics this summer. <br />
|-<br />
| [[Image:Isui.JPG|100px|left|Daniel Isui]]|| Daniel Isui Aguilar Salvador || Biomedical Research, Instituto de Investigaciones Biomédicas, Proudly UNAM. I'm an undergrad student on Biomedical Research (whatever that is), and I'm interested in original ways to apply biology. Since I was absent during part of the development of the project my work consisted in some lab work, but mainly I focused on the development of the single cell model and the kinetics implied on it. As well as in synthesizing the project to upload it to the wiki.<br />
|-<br />
| [[Image:Gil-mx-18.jpg|100px]] || Gilberto Gomez Correa || Physics, Facultad de ciencias, UNAM. My interest in synthetic biology is in the posible applications and the extent of them to every area of human action in particular its integration with biodegradation research and with neuroscience. My role in the team was as a multitask member mainly doing laboratory work, modeling in paper and in the computer and helping with the coordination of the project.<br />
<br />
|- <br />
| [[Image:Jose1.jpg|100px]]|| José Martínez Lomeli || Physics - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:Cjdg.png|100px]]|| [http://openwetware.org/wiki/User:Cristian_Delgado Cristian J. Delgado G.] || Undergraduate Biology Student Faculty of Sciences UNAM. work in rare and strange fields for biology, bionanotecnology, biomimetics, biorobotics, biological based devices, bio art, and anything that can be with "BIO",i believe that we dont have to close our view just on one side and turn back again to nature.On night i turn into dj and producer and i enjoy city night life. I love gadgets :D and computers, what else could make weird sounds and music?<br />
|-<br />
| [[Image:Pancho.jpg|100px|left|Pancho]] || Francisco Javier Razo Hernández || Plants Biotechnology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
| [[Image:Iledelaf.JPG|100px|left]] || Ileana de la Fuente Colmenares || Biology - Facultad de Ciencias, UNAM. I'm interested in designing biofuel cells from modificated microorganisms with rare metabolisms in relation with biorremediaton procesess and their implementation in Mexico. My roll in the Turing proyect was as a helper. I reviewed references and bibliography for the bioparts design and their characterization. <br />
|-<br />
| || Alin Acuña Alonzo || Biology - Facultad de Ciencias, UNAM<br />
|- <br />
| || Román Alfonso Acosta Díaz || Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Eniak Hernandez || Biology - Facultad de Ciencias, UNAM<br />
|}<br />
<br />
<br />
<h2> Advisors </h2><br />
<br />
{|<br />
|Elias Samra-Hassan || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|[[Image:Dr. Alexander de Luna Fors.jpg|100px]] || Alexander de Luna Fors || Molecular Biology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
|}<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1>[[Image:Month-icon.png | 50px]] Team moments </h1><br />
<br />
[[Image:México_CINVESTAV_1.JPG|center|700px|thumb|Team at lab in Langebio Cinvestav. In order of apparence, Jesus Pérez, Francisco Razo, Gilberto Gomez, Alexander De Luna, Roman Alfonso, Luis Martínez]]<br />
<br />
<br />
[[Image:Equipo21Agos09MX.jpg|center|700px|thumb|Team at Faculty of Sciences UNAM]]<br />
<br />
<br />
===Powered by Mexican Patriotic Power[https://static.igem.org/mediawiki/2009/6/66/Mexico_rules.jpg .]===<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T01:01:50Z<p>LUIS DE JESUS: Descripciones</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and Projects===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module and Status<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator.<br />
|-<br />
| '''Mod 2 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR.<br />
|-<br />
| '''Mod 3 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4 Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Projects====<br />
<br />
<center><br />
{| border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
| Complex Quorum sensing circuit that receives the signal of PAI+LasR and AI+LuxR to control the production of LuxI and LasI enzymes. <br />
|-<br />
| '''Pending'''<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
| Tet constitutive inverter controlling LasR expression and Lac constitutive inverter controlling LuxR expression.<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Status<br />
! Biobrick Name<br />
! Image<br />
! Description<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
| LasR coding region and a double terminator.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the expresion of LasI enzyme, no terminator. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter. <br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
| The BBa_J23100 constitutive promoter with Lac systems inverter and strong RBS.<br />
|-<br />
| '''Sent'''<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
| POPS regulated and Lac inverter system with strong RBS. <br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/PartsTeam:IPN-UNAM-Mexico/Parts2009-10-22T00:51:24Z<p>LUIS DE JESUS: Descripciones</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<h1>Biobricks </h1><br />
<br />
==[[Image:Month-icon.png | 50px]]Biobricks==<br />
<br />
We contribute to the registry with 11 new biobricks, 5 of them are favorite biobricks from the team and in this section we document them:<br />
===Main biobricks: modules and favorites===<br />
<br />
====Modules====<br />
<br />
<br />
<br />
<center><br />
{| border="1"<br />
! Module<br />
! Biobrick Name<br />
! Type<br />
! Image<br />
! Description<br />
|-<br />
| '''Mod 1'''<br />
| '''[http://partsregistry.org/Part:BBa_K266006 BBa_K266006]'''<br />
| '''Las AHL'''<br />
| [[Image:AI LasI.jpg|400px|left|Las AHL]]<br />
| BBa_K091146 promoter (PAI+LasR inducible & AI+LuxR repressible) controls the policistronic expresion of LasI enzyme and GFP, double terminator<br />
|-<br />
| '''Mod 2'''<br />
| '''[http://partsregistry.org/Part:BBa_K266004 BBa_K266004]''' <br />
| '''Lac inverter'''<br />
| [[Image:AI Lac.jpg|500px|left|Lac Inverter]]<br />
| Constitutive promoter J23100 with Lac system inverter controlling the expression of LasR <br />
|-<br />
| '''Mod 3'''<br />
| '''[http://partsregistry.org/Part:BBa_K266001 BBa_K266001]'''<br />
| '''Tet inverter'''<br />
| [[Image:AI Tet.jpg|500px|left|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
| J23100 constitutive promoter directs the expression of tetracycline repressor (TetR). TetR binds to pTet regulatory region resulting in a negative control of the production of LuxR. The whole system acts as an Inverter of Tet system controlling LuxR expression. TetR repression is inhibited by the addition of tetracycline or its analog, aTc. <br />
|-<br />
| '''Mod 4'''<br />
| '''[http://partsregistry.org/Part:BBa_K266000 BBa_K266000]'''<br />
| '''Lux AHL'''<br />
| [[Image:AI LuxI.jpg|300px|left|Lux AHL]]<br />
| This biobrick has a promoter inducible by PAI+LasR (BBa_R0079) I.e. positive regulation and produces LuxI enzyme (BBa_F1610). This enzyme produces 3OC6HSL (AI). <br />
|}<br />
</center><br />
<br />
<br />
====Favorites====<br />
<br />
<center><br />
{| border="1"<br />
! Biobrick Name<br />
! Image<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266007 BBa_K266007]'''<br />
| [[Image:BBa K266007.jpg|500px|left|substrates]]<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266010 BBa_K2660010]'''<br />
| [[Image:BBa K266010.jpg|500px|left|substrates]]<br />
|-<br />
|}<br />
</center><br />
<br />
===Auxiliary biobricks===<br />
<br />
<center><br />
<br />
{|border="1"<br />
! Biobrick Name<br />
! Image<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266002 BBa_K266002]'''<br />
| [[Image:BBa K266002.jpg|150px|left|substrates]]<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266005 BBa_K266005]'''<br />
| [[Image:BBa K266005.jpg|150px|left|substrates]]<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266008 BBa_K266008]'''<br />
| [[Image:BBa K266008.jpg|400px|left|substrates]]<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266009 BBa_K266009]'''<br />
| [[Image:BBa K266009.jpg|500px|left|substrates]]<br />
|-<br />
| '''[http://partsregistry.org/Part:BBa_K266011 BBa_K2660011]'''<br />
| [[Image:BBa K266011.jpg|300px|left|substrates]]<br />
<br />
|}<br />
<br />
</center><br />
<br />
==[[Image:Month-icon.png | 50px]]Plasmids==<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/TeamTeam:IPN-UNAM-Mexico/Team2009-10-22T00:43:14Z<p>LUIS DE JESUS: /* Powered by Mexican Patriotic Power */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<h1>[[Image:Month-icon.png | 50px]] About us</h1><br />
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<h1>[[Image:Month-icon.png | 50px]] Team members</h1><br />
<h2> Instructors </h2><br />
<br />
{| style=" border="0"<br />
|- <br />
| [[Image:PadillaLongoria.jpg|left|100px|Pablo Padilla Longoria]] || Pablo Padilla Longoria || Mathematics - Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), UNAM<br />
|-<br />
<br />
| || Fabiola Ramirez Corona || Molecular Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Arturo Becerra || Origin of Life - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:fhq.jpg|left|100px|Francisco Quiroz]] || Francisco Hernández Quiroz || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|}<br />
<br />
<h2> Students </h2><br />
<br />
{|<br />
|-<br />
| [[Image:Luis_Mtz.jpg|100px|left|Luis Martínez]]|| '''[http://openwetware.org/wiki/User:Luis_De_Jesus_Martinez Luis de Jesús Martínez Lomeli]''' || Mathematics - Facultad de Ciencias, UNAM. As an undergraduate math student my main interest in synthetic biology is develop biological systems that could give a new perspective about mathematical models (e.g. our project). My main role in the team was design the synthetic genetic network of biobricks that fulfill Turing hypothesis to generate spatiotemporal patterns. Besides, coordinate the whole project, work in the implementation of the system at lab, assist in the development of the model and stablish the colaboration with the LCG-UNAM mexican team. Lot of work! =)<br />
|-<br />
| [[Image:Chucho.jpg|100px]] || Jesús Pérez Juárez || Biology - Facultad de Ciencias, UNAM. I’m Jesús I study fourth year biology I'm so intersting in live sciences I think is a great oportunity to interdisciplinary collaborations and new aplications, I've realy enjoied the work with pysics and mathematics this summer. <br />
|-<br />
| [[Image:Isui.JPG|100px|left|Daniel Isui]]|| Daniel Isui Aguilar Salvador || Biomedical Research, Instituto de Investigaciones Biomédicas, Proudly UNAM. I'm an undergrad student on Biomedical Research (whatever that is), and I'm interested in original ways to apply biology. Since I was absent during part of the development of the project my work consisted in some lab work, but mainly I focused on the development of the single cell model and the kinetics implied on it. As well as in synthesizing the project to upload it to the wiki.<br />
|-<br />
| [[Image:Gil-mx-18.jpg|100px]] || Gilberto Gomez Correa || Physics, Facultad de ciencias, UNAM. My interest in synthetic biology is in the posible applications and the extent of them to every area of human action in particular its integration with biodegradation research and with neuroscience. My role in the team was as a multitask member mainly doing laboratory work, modeling in paper and in the computer and helping with the coordination of the project.<br />
<br />
|- <br />
| [[Image:Jose1.jpg|100px]]|| José Martínez Lomeli || Physics - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:Cjdg.png|100px]]|| [http://openwetware.org/wiki/User:Cristian_Delgado Cristian J. Delgado G.] || Undergraduate Biology Student Faculty of Sciences UNAM. work in rare and strange fields for biology, bionanotecnology, biomimetics, biorobotics, biological based devices, bio art, and anything that can be with "BIO",i believe that we dont have to close our view just on one side and turn back again to nature.On night i turn into dj and producer and i enjoy city night life. I love gadgets :D and computers, what else could make weird sounds and music?<br />
|-<br />
| [[Image:Pancho.jpg|100px|left|Pancho]] || Francisco Javier Razo Hernández || Plants Biotechnology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
| [[Image:Iledelaf.JPG|100px|left]] || Ileana de la Fuente Colmenares || Biology - Facultad de Ciencias, UNAM. I'm interested in designing biofuel cells from modificated microorganisms with rare metabolisms in relation with biorremediaton procesess and their implementation in Mexico. My roll in the Turing proyect was as a helper. I reviewed references and bibliography for the bioparts design and their characterization. <br />
|-<br />
| || Alin Acuña Alonzo || Biology - Facultad de Ciencias, UNAM<br />
|- <br />
| || Román Alfonso Acosta Díaz || Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Eniak Hernandez || Biology - Facultad de Ciencias, UNAM<br />
|}<br />
<br />
<br />
<h2> Advisors </h2><br />
<br />
{|<br />
|Elias Samra-Hassan || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|[[Image:Dr. Alexander de Luna Fors.jpg|100px]] || Alexander de Luna Fors || Molecular Biology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
|}<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1>[[Image:Month-icon.png | 50px]] Team moments </h1><br />
<br />
[[Image:México_CINVESTAV_1.JPG|center|700px|thumb|Team at lab in Langebio Cinvestav. In order of apparence, Jesus Pérez, Francisco Razo, Gilberto Gomez, Alexander De Luna, Roman Alfonso, Luis Martínez]]<br />
<br />
<br />
[[Image:Equipo21Agos09MX.jpg|center|700px|thumb|Team at Faculty of Sciences UNAM]]<br />
<br />
<br />
===Powered by Mexican Patriotic Power[https://static.igem.org/mediawiki/2009/6/66/Mexico_rules.jpg .]===<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/TeamTeam:IPN-UNAM-Mexico/Team2009-10-22T00:41:23Z<p>LUIS DE JESUS: </p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<h1>[[Image:Month-icon.png | 50px]] About us</h1><br />
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<h1>[[Image:Month-icon.png | 50px]] Team members</h1><br />
<h2> Instructors </h2><br />
<br />
{| style=" border="0"<br />
|- <br />
| [[Image:PadillaLongoria.jpg|left|100px|Pablo Padilla Longoria]] || Pablo Padilla Longoria || Mathematics - Instituto de Investigaciones en Matemáticas Aplicadas y Sistemas (IIMAS), UNAM<br />
|-<br />
<br />
| || Fabiola Ramirez Corona || Molecular Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Arturo Becerra || Origin of Life - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:fhq.jpg|left|100px|Francisco Quiroz]] || Francisco Hernández Quiroz || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|}<br />
<br />
<h2> Students </h2><br />
<br />
{|<br />
|-<br />
| [[Image:Luis_Mtz.jpg|100px|left|Luis Martínez]]|| '''[http://openwetware.org/wiki/User:Luis_De_Jesus_Martinez Luis de Jesús Martínez Lomeli]''' || Mathematics - Facultad de Ciencias, UNAM. As an undergraduate math student my main interest in synthetic biology is develop biological systems that could give a new perspective about mathematical models (e.g. our project). My main role in the team was design the synthetic genetic network of biobricks that fulfill Turing hypothesis to generate spatiotemporal patterns. Besides, coordinate the whole project, work in the implementation of the system at lab, assist in the development of the model and stablish the colaboration with the LCG-UNAM mexican team. Lot of work! =)<br />
|-<br />
| [[Image:Chucho.jpg|100px]] || Jesús Pérez Juárez || Biology - Facultad de Ciencias, UNAM. I’m Jesús I study fourth year biology I'm so intersting in live sciences I think is a great oportunity to interdisciplinary collaborations and new aplications, I've realy enjoied the work with pysics and mathematics this summer. <br />
|-<br />
| [[Image:Isui.JPG|100px|left|Daniel Isui]]|| Daniel Isui Aguilar Salvador || Biomedical Research, Instituto de Investigaciones Biomédicas, Proudly UNAM. I'm an undergrad student on Biomedical Research (whatever that is), and I'm interested in original ways to apply biology. Since I was absent during part of the development of the project my work consisted in some lab work, but mainly I focused on the development of the single cell model and the kinetics implied on it. As well as in synthesizing the project to upload it to the wiki.<br />
|-<br />
| [[Image:Gil-mx-18.jpg|100px]] || Gilberto Gomez Correa || Physics, Facultad de ciencias, UNAM. My interest in synthetic biology is in the posible applications and the extent of them to every area of human action in particular its integration with biodegradation research and with neuroscience. My role in the team was as a multitask member mainly doing laboratory work, modeling in paper and in the computer and helping with the coordination of the project.<br />
<br />
|- <br />
| [[Image:Jose1.jpg|100px]]|| José Martínez Lomeli || Physics - Facultad de Ciencias, UNAM<br />
|-<br />
| [[Image:Cjdg.png|100px]]|| [http://openwetware.org/wiki/User:Cristian_Delgado Cristian J. Delgado G.] || Undergraduate Biology Student Faculty of Sciences UNAM. work in rare and strange fields for biology, bionanotecnology, biomimetics, biorobotics, biological based devices, bio art, and anything that can be with "BIO",i believe that we dont have to close our view just on one side and turn back again to nature.On night i turn into dj and producer and i enjoy city night life. I love gadgets :D and computers, what else could make weird sounds and music?<br />
|-<br />
| [[Image:Pancho.jpg|100px|left|Pancho]] || Francisco Javier Razo Hernández || Plants Biotechnology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
| [[Image:Iledelaf.JPG|100px|left]] || Ileana de la Fuente Colmenares || Biology - Facultad de Ciencias, UNAM. I'm interested in designing biofuel cells from modificated microorganisms with rare metabolisms in relation with biorremediaton procesess and their implementation in Mexico. My roll in the Turing proyect was as a helper. I reviewed references and bibliography for the bioparts design and their characterization. <br />
|-<br />
| || Alin Acuña Alonzo || Biology - Facultad de Ciencias, UNAM<br />
|- <br />
| || Román Alfonso Acosta Díaz || Biology - Facultad de Ciencias, UNAM<br />
|-<br />
| || Eniak Hernandez || Biology - Facultad de Ciencias, UNAM<br />
|}<br />
<br />
<br />
<h2> Advisors </h2><br />
<br />
{|<br />
|Elias Samra-Hassan || Computer Science - Facultad de Ciencias, UNAM<br />
|-<br />
|[[Image:Dr. Alexander de Luna Fors.jpg|100px]] || Alexander de Luna Fors || Molecular Biology - Laboratorio Nacional de Genómica para la Biodiversidad (LANGEBIO), CINVESTAV IRAPUATO<br />
|-<br />
|}<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1>[[Image:Month-icon.png | 50px]] Team moments </h1><br />
<br />
[[Image:México_CINVESTAV_1.JPG|center|700px|thumb|Team at lab in Langebio Cinvestav. In order of apparence, Jesus Pérez, Francisco Razo, Gilberto Gomez, Alexander De Luna, Roman Alfonso, Luis Martínez]]<br />
<br />
<br />
[[Image:Equipo21Agos09MX.jpg|center|700px|thumb|Team at Faculty of Sciences UNAM]]<br />
<br />
<br />
===Powered by [https://2009.igem.org/Image:Mexico_rules.jpg Mexican Patriotic Power]===<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:23:01Z<p>LUIS DE JESUS: better order</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]] Theoretical Results==<br />
As we could see in the first simulations in Comsol Multiphysics, with our estimated diffusion coefficients and the classical activator inhibitor dynamic equations, we recovered a spotted pattern.<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Experimental Results==<br />
<br />
r<br />
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s<br />
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u<br />
<br />
l<br />
<br />
t<br />
<br />
s<br />
<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
<br />
We were able to build most of our original design (1 biobrick ligation remaining) and to experimentally test the functioning of one of our regulatory modules coupled to the autocathalytic module.<br />
<br />
Besides having one regulatory module working as expected we also have the support from our models on the formation at least of spatiotemporal instabilities, this sustents the validity of our design on its potential to emulate an activator-inhibitor system. <br />
<br />
The fact that our designed system is able to behave in this way under certain conditions provided by the regulatory modules shows that the original assumptions on A. Turing’s model have the potential to naturally have emerged in living organisms during evolution, and to be the underlying mechanism by which some of the naturally founded patterns are formed during morphogenesis.<br />
<br />
We also realized during the implementation of the project that there are some details, both on the modelling and in the design, we could improve to make a better approximation of the activator-inhibitor system.<br />
<br />
We are very excited about the reachings that our project could have if we can successfully implement it, and our results show we are going on the right direction.<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
As extensions of our project we are planning to work with this biobricks system in eucariotic tissues and replace de IPTG and ATC depedence with another kind of synthetic morphogens and the ''E. colis'' with GFP with melanocytes. To reproduce pigmentation patterns and fully demostrate the turing work and give great results in developmental biology.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:19:31Z<p>LUIS DE JESUS: /* 50pxFinal Conclusions */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
===Theoretical Results===<br />
As we could see in the first simulations in Comsol Multiphysics, with our estimated diffusion coefficients and the classical activator inhibitor dynamic equations, we recovered a spotted pattern.<br />
<br />
===Lab Results===<br />
<br />
r<br />
<br />
e<br />
<br />
s<br />
<br />
u<br />
<br />
l<br />
<br />
t<br />
<br />
s<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
<br />
We were able to build most of our original design (1 biobrick ligation remaining) and to experimentally test the functioning of one of our regulatory modules coupled to the autocathalytic module.<br />
<br />
Besides having one regulatory module working as expected we also have the support from our models on the formation at least of spatiotemporal instabilities, this sustents the validity of our design on its potential to emulate an activator-inhibitor system. <br />
<br />
The fact that our designed system is able to behave in this way under certain conditions provided by the regulatory modules shows that the original assumptions on A. Turing’s model have the potential to naturally have emerged in living organisms during evolution, and to be the underlying mechanism by which some of the naturally founded patterns are formed during morphogenesis.<br />
<br />
We also realized during the implementation of the project that there are some details, both on the modelling and in the design, we could improve to make a better approximation of the activator-inhibitor system.<br />
<br />
We are very excited about the reachings that our project could have if we can successfully implement it, and our results show we are going on the right direction.<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
As extensions of our project we are planning to work with this biobricks system in eucariotic tissues and replace de IPTG and ATC depedence with another kind of synthetic morphogens and the ''E. colis'' with GFP with melanocytes. To reproduce pigmentation patterns and fully demostrate the turing work and give great results in developmental biology.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:16:34Z<p>LUIS DE JESUS: </p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
===Theoretical Results===<br />
As we could see in the first simulations in Comsol Multiphysics, with our estimated diffusion coefficients and the classical activator inhibitor dynamic equations, we recovered a spotted pattern.<br />
<br />
===Lab Results===<br />
<br />
r<br />
<br />
e<br />
<br />
s<br />
<br />
u<br />
<br />
l<br />
<br />
t<br />
<br />
s<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
<br />
We were able to build most of our original design and to experimentally test the functioning of one of our regulatory modules coupled to the autocathalytic module.<br />
<br />
Besides having one regulatory module working as expected we also have the support form our models on the formation at least of spatiotemporal instabilities, this sustents the validity of our design on its potential to emulate an activator-inhibitor system. <br />
<br />
The fact that our designed system is able to behave in this way under certain conditions provided by the regulatory modules shows that the original assumptions on A. Turing’s model have the potential to naturally have emerged in living organisms during evolution, and to be the underlying mechanism by wich some of the naturally founded patterns are formed during morphogenesis.<br />
<br />
We also realized during the implementation of the project that there are some details, both on the modelling and in the design, we could improve to make a better approximation of the activator-inhibitor system.<br />
<br />
We are very excited about the reachings that our project could have if we can successfully implement it, and our results show we are going on the right direction.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
As extensions of our project we are planning to work with this biobricks system in eucariotic tissues and replace de IPTG and ATC depedence with another kind of synthetic morphogens and the ''E. colis'' with GFP with melanocytes. To reproduce pigmentation patterns and fully demostrate the turing work and give great results in developmental biology.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:15:27Z<p>LUIS DE JESUS: /* Preliminary Lab Results */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
===Theoretical Results===<br />
As we could see in the first simulations in Comsol Multiphysics, with our estimated diffusion coefficients and the classical activator inhibitor dynamic equations, we recovered a spotted pattern.<br />
<br />
===Lab Results===<br />
<br />
r<br />
<br />
e<br />
<br />
s<br />
<br />
u<br />
<br />
l<br />
<br />
t<br />
<br />
s<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
==[[Image:Month-icon.png | 50px]]Lab results==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
As extensions of our project we are planning to work with this biobricks system in eucariotic tissues and replace de IPTG and ATC depedence with another kind of synthetic morphogens and the ''E. colis'' with GFP with melanocytes. To reproduce pigmentation patterns and fully demostrate the turing work and give great results in developmental biology.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:14:37Z<p>LUIS DE JESUS: /* 50pxPreliminary results */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
===Theoretical Results===<br />
As we could see in the first simulations in Comsol Multiphysics, with our estimated diffusion coefficients and the classical activator inhibitor dynamic equations, we recovered a spotted pattern.<br />
<br />
===Preliminary Lab Results===<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
==[[Image:Month-icon.png | 50px]]Lab results==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
As extensions of our project we are planning to work with this biobricks system in eucariotic tissues and replace de IPTG and ATC depedence with another kind of synthetic morphogens and the ''E. colis'' with GFP with melanocytes. To reproduce pigmentation patterns and fully demostrate the turing work and give great results in developmental biology.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:12:34Z<p>LUIS DE JESUS: /* 50pxFurther work */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
==[[Image:Month-icon.png | 50px]]Lab results==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
As extensions of our project we are planning to work with this biobricks system in eucariotic tissues and replace de IPTG and ATC depedence with another kind of synthetic morphogens and the ''E. colis'' with GFP with melanocytes. To reproduce pigmentation patterns and fully demostrate the turing work and give great results in developmental biology.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:08:57Z<p>LUIS DE JESUS: /* 50pxFurther work */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
==[[Image:Month-icon.png | 50px]]Lab results==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ResultsTeam:IPN-UNAM-Mexico/Results2009-10-22T00:04:25Z<p>LUIS DE JESUS: /* 50pxFurther work */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
<br />
==[[Image:Month-icon.png | 50px]]Preliminary results==<br />
<br />
==[[Image:Month-icon.png | 50px]]Modelling results==<br />
<br />
We believe the modelling part of our project is a very strong component of it. First of all, the system was designed to fulfill the requirements of a theoretical proposal by A. Turing of a reaction-diffusion model on morphogenesis, more specifically an activator-inhibitor system. These requirements were checked by calculating and using the diffusive properties of the components involved (AHLs) in our system on the Geirer and Meihnardt model of activator-inhibitor, successfully predicting the generation of patterns in our design.<br />
<br />
Later, we wanted to recreate the generation of a pattern from its very biochemical basis to be able to predict under what conditions the pattern would form and how it would be, so we described all the biochemical steps involved in our network (form transcription to complexes formation) by constructing a kinetic model with parameters available in the literature. From this kinetic model we derived our ordinary differential equations and used it to make a spatial simulation of the behavior of a colony, predicting the formation of some kind of instability but not yet a spatiotemporal pattern. <br />
<br />
Even when there was no explicit pattern formation on the detailed model, we did obvserve it in our simulation of the general model of activator-inhibitor; so we will explore in the future other approaches to figer out if the predictions of this model are conclusive or not, like stochastic approaches. And we will also have to compare these results with the experimental results that we will obtain with the fully implemented system.<br />
<br />
==[[Image:Month-icon.png | 50px]]Lab results==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Final Conclusions==<br />
1<br />
<br />
2<br />
<br />
3<br />
<br />
==[[Image:Month-icon.png | 50px]]Further work==<br />
<br />
The first step after the Jamboree will be finish our last biobricks ligation and. With this we can test our system in different conditions and concentrations of IPTG and ATC and characterize part relative to the whole net. Then we can really see if our system was really working as we thought it should.<br />
Besides we need to find a different approach to model mathematically the interactions that take part in the project in order to predict its behavior.<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T23:57:45Z<p>LUIS DE JESUS: /* The work of Turing */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
[[Image:Zebra.jpg|thumb|200px|zebra stripes pattern]]<br />
[[Image:Leopard.jpg|thumb|200px|leopard spots pattern]]<br />
<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
There are some variants of the classical Activator-Inhibitor system, like the Activator-Inhibitor with Substrates. Those systems describe the aditional existence of a substance that is degraded or inactivated along the time and the production of the activator is limited to its availability. This kind of substrates can sometimes play the role of the inhibitor, and due to this duality we can model our project in several ways with no loss of generality.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has became in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could behave as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradients of morphogens in the media and have the potential to accordingly differentially respond. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfills the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book literaly says : <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
<br />
an advise that few teams in the past years' competitions may have considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Meinhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that genes of the quorum system ''las'' will have the role of the Activator, while genes of the ''lux'' quorum system are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'', ''Las'' and ''AI'', ''PAI'' lactones respectively. This compounds are very small and travel through the membrane rapidly diffusing in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''. in our genetic network the cell will differentially respond to the different concentrations in the gradients of ''PAI'' and ''AI'' by expressing different levels of ''GFP''.<br />
<br />
<br />
We also used a constitutive ''Lac'' inverter that allows us to control the production of ''LasR'' with ''IPTG'' and a constitutive ''Tet'' inverter that allows us to control ''LuxR'' with ''aTc. ''The controlling system of inverters provide a good way to make more sensitive the parameters adjustment.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to be controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the BioBricks system works?, in this subsection we will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its controlling promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, and if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Synthesizing===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because it recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farther place the inhibitory morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T23:57:20Z<p>LUIS DE JESUS: /* The work of Turing */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
[[Image:Zebra.jpg|thumb|200px|zebra stripes pattern]]<br />
[[Image:Leopard.jpg|thumb|200px|zebra stripes pattern]]<br />
<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
There are some variants of the classical Activator-Inhibitor system, like the Activator-Inhibitor with Substrates. Those systems describe the aditional existence of a substance that is degraded or inactivated along the time and the production of the activator is limited to its availability. This kind of substrates can sometimes play the role of the inhibitor, and due to this duality we can model our project in several ways with no loss of generality.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has became in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could behave as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradients of morphogens in the media and have the potential to accordingly differentially respond. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfills the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book literaly says : <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
<br />
an advise that few teams in the past years' competitions may have considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Meinhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that genes of the quorum system ''las'' will have the role of the Activator, while genes of the ''lux'' quorum system are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'', ''Las'' and ''AI'', ''PAI'' lactones respectively. This compounds are very small and travel through the membrane rapidly diffusing in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''. in our genetic network the cell will differentially respond to the different concentrations in the gradients of ''PAI'' and ''AI'' by expressing different levels of ''GFP''.<br />
<br />
<br />
We also used a constitutive ''Lac'' inverter that allows us to control the production of ''LasR'' with ''IPTG'' and a constitutive ''Tet'' inverter that allows us to control ''LuxR'' with ''aTc. ''The controlling system of inverters provide a good way to make more sensitive the parameters adjustment.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to be controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the BioBricks system works?, in this subsection we will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its controlling promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, and if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Synthesizing===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because it recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farther place the inhibitory morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/File:Leopard.jpgFile:Leopard.jpg2009-10-21T23:55:16Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/File:Zebra.jpgFile:Zebra.jpg2009-10-21T23:54:56Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T23:25:29Z<p>LUIS DE JESUS: /* The Activator-Inhibitor */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
There are some variants of the classical Activator-Inhibitor system, like the Activator-Inhibitor with substrates. Those systems describe the aditional existance of a sustance that is degraded or inactivated along time and the production of the activator is limited to its existance. This kind of substrates can play the role of the inhibitor sometimes and due to this duality we can model our project in several ways with no loss of generality.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has became in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could behave as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradients of morphogens in the media and have the potential to accordingly differentially respond. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfills the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book literaly says : <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
<br />
an advise that few teams in the past years' competitions may have considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Meinhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that genes of the quorum system ''las'' will have the role of the Activator, while genes of the ''lux'' quorum system are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'', ''Las'' and ''AI'', ''PAI'' lactones respectively. This compounds are very small and travel through the membrane rapidly diffusing in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''. in our genetic network the cell will differentially respond to the different concentrations in the gradients of ''PAI'' and ''AI'' by expressing different levels of ''GFP''.<br />
<br />
<br />
We also used a constitutive ''Lac'' inverter that allows us to control the production of ''LasR'' with ''IPTG'' and a constitutive ''Tet'' inverter that allows us to control ''LuxR'' with ''aTc. ''The controlling system of inverters provide a good way to make more sensitive the parameters adjustment.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to be controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the BioBricks system works?, in this subsection we will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its controlling promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, and if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Resuming===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because it recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farther place the inhibitory morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T23:16:44Z<p>LUIS DE JESUS: /* checar lode sustrato */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has became in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could behave as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradients of morphogens in the media and have the potential to accordingly differentially respond. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfills the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book literaly says : <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
<br />
an advise that few teams in the past years' competitions may have considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Meinhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that genes of the quorum system ''las'' will have the role of the Activator, while genes of the ''lux'' quorum system are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'', ''Las'' and ''AI'', ''PAI'' lactones respectively. This compounds are very small and travel through the membrane rapidly diffusing in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''. in our genetic network the cell will differentially respond to the different concentrations in the gradients of ''PAI'' and ''AI'' by expressing different levels of ''GFP''.<br />
<br />
<br />
We also used a constitutive ''Lac'' inverter that allows us to control the production of ''LasR'' with ''IPTG'' and a constitutive ''Tet'' inverter that allows us to control ''LuxR'' with ''aTc. ''The controlling system of inverters provide a good way to make more sensitive the parameters adjustment.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to be controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the BioBricks system works?, in this subsection we will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its controlling promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, and if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Resuming===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because it recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farther place the inhibitory morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/File:Mexicoflag.jpgFile:Mexicoflag.jpg2009-10-21T22:52:12Z<p>LUIS DE JESUS: </p>
<hr />
<div></div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:59:19Z<p>LUIS DE JESUS: /* 50pxMorphogenesis qualitative mechanisms */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Resuming===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farter place que inhibitor morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:58:54Z<p>LUIS DE JESUS: </p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
<br />
[[Image:ACT-INH.jpg|center|200px|Activator-Inhibitor dynamics]]<br />
<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Resuming===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farter place que inhibitor morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:55:53Z<p>LUIS DE JESUS: </p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
[[Image:Curv ACT-INH.jpg |200px|center|Local activation & longe range inhibition]]<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''"Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve."''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Resuming===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farter place que inhibitor morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:49:28Z<p>LUIS DE JESUS: /* 50px The Activator-Inhibitor system on biobricks: The dynamics */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
===Resuming===<br />
<br />
The project of the IPN-UNAM-MEXICO team will provide biological evidence of a classical theoretical work of morphogenesis by means of synthetic biology. The biobricks synthetic network that we propose recover the qualitative requeriments to generate a spatiotemporal pattern because recognize at least two differente morphogens ''Lux AHL'' and ''Las AHL'', they diffuse with different rates, we can give a non-homogeneous starting point to the area where the morphogens will interact and diffuse with IPTG and ATC; and in areas where there are enough substrates IPTG and ATC those zones can remain activated while in a farter place que inhibitor morphogen will predomain. Hence our biobricks system is of reaction-diffusion-substrate type.<br />
For more information check de [[Team:IPN-UNAM-Mexico/Modeling | modeling]], [[Team:IPN-UNAM-Mexico/Modeling | parts]] and [[Team:IPN-UNAM-Mexico/Results | results]] sections.<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:35:24Z<p>LUIS DE JESUS: /* Complete system */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|Biobricks system]]<br />
<br />
The two sequences from below in the picture represents the biobricks before described but in a particular order for easy work at lab only.<br />
<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:27:31Z<p>LUIS DE JESUS: /* Diffusion */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modeling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:25:44Z<p>LUIS DE JESUS: /* Diffusion */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL'' will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modelling | modelling section]]) which covers one of the requests for generating patterns (see above).<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T21:24:44Z<p>LUIS DE JESUS: /* 50px The Activator-Inhibitor system on biobricks: The dynamics */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
If we suppose that ''LacI ''is no produced, then the ''Lac'' promoter will produce ''LasR'', if this happens, and the colony of ''E. coli'' is big enough to achieve a threshold of activation, a phenomena of positive feedback will start by ''LasR''+''PAI'', the last one produced by ''LasI enzyme''. This complex will induce the double promoter, the ''GFP'' will be overexpressed and much more ''LAS AHL'' will be released. A local Activation will take place.<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Later ''LuxI'' enzyme will be produced by the efect of ''LasR''+''PAI'' on its control promoter, and ''Lux AHL'' will become released.<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
When there is enough ''Lux AHL ''to achieve a second threshold, an if we supose that the ''tet'' promoter is not repressed, ''LuxR'' will be produced, forming a complex with ''Lux AHL'', ''LuxR ''+ ''AI ''which in turn will repress de double promoter. The Longe range inhibition will take place.<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
Just by molecular weights, the ''3OC12HSL'' from ''Las AHL'' and ''3OC6HSL'' from ''Lux AHL,'' the ''Lux AHL''<nowiki> will diffuse faster, (check [[Team:IPN-UNAM-Mexico/Modelling | modelling section]]) which covers one of the requests for generating patterns (see above).</nowiki><br />
<br />
<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
IPTG and ATC in the media will provide the characteristics of limiting substrates because if any of them is missing simply ''LuxR'' or ''LasR'' will not be produced because of the inverters that control them, and no interaction by quorum sensing will be possible, i.e., the reaction and diffusion part will not work and the system should arrive to an steady state.<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T20:54:00Z<p>LUIS DE JESUS: /* 50pxReaction-Diffusion systems implemented on Biobricks */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
<br />
<br />
The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
<br />
<br />
The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
<br />
<br />
The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
<br />
<br />
<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
<br />
an advise that few teams in the past years' competitions may have considered considered.<br />
<br />
==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
<br />
Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. Our proposal is that the quorum system genes ''LAS'' will have the role of the Activator, ''Lux'' quorum system genes are going to be the Inhibitors and ''IPTG'' and ''ATC'' will be the substrates that will delimit de pattern. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
<br />
<br />
<br />
===Reaction - Diffusion===<br />
<br />
We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
<br />
<br />
We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
<br />
<br />
We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
<br />
<br />
For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
<br />
<br />
The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
<br />
<br />
The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
<br />
[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
<br />
<br />
This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
<br />
<br />
<br />
===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
<br />
[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
<br />
<br />
This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
<br />
<br />
===Substrates===<br />
<br />
===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
<br />
[[Image:AI substrates.jpg|500px|center|substrates]]<br />
<br />
<br />
Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
<br />
==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
<br />
The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
<br />
<br />
==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
First, we idenfify <br />
<br />
<br />
<br />
==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|texto descriptivo]]<br />
<br />
<br />
<br />
<br />
{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUShttp://2009.igem.org/Team:IPN-UNAM-Mexico/ProjectTeam:IPN-UNAM-Mexico/Project2009-10-21T20:49:35Z<p>LUIS DE JESUS: /* 50px The Activator-Inhibitor system on biobricks: The dynamics */</p>
<hr />
<div>{{Template:IPN-UNAM-Mexico}}<br />
__NOTOC__<br />
<br />
<center><h1>Turing meets synthetic biology</h1></center><br />
<br />
==[[Image:Month-icon.png | 50px]]Introduction==<br />
<br />
===The work of Turing===<br />
<br />
In 1952 Alan M. Turing in his classical paper called ''The chemical basis of morphogenesis '' he sugested that "...a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis." This system is amazing by its simplicity. With only two morphogens it's possible to reproduce nontrivial patterns that are similar to those of zebras or leopards.<br />
<br />
Although there is not enough evidence of the existence of these morphogens in living organisms, the likeliness of the patterns obtained by theoretical means using this model with the ones found in nature is astonishing.<br />
<br />
Turing assumed that the morphogenes can react with each other and diffuse through cells. It is necessary that at the beginning there is a non-homogeneous distribuition of these morphogenes, which is often called chemical prepattern and can be given merely by random disturbances. An intuitive notion would tell us that the diffusion of the morphogenes starting from this chemical prepattern would led to a homogenous state of the system, but surprisingly the Turing proposal says that non-homgenous structures will arise, as a direct consequence of diffusion (the turing hyphotesis); reaching a stable state with regions with high concentrantions of one morphogen and regions with high concentration of the others. This non-homogeneous distribuition patterns of morphogens resembles those found in nature during some stages of morhpogenesis (from the gastrulation or the tentacle patterns on hydras to the jaguar spots).<br />
<br />
===Reaction-Diffusion equations===<br />
<br />
Turing formally described his proposal with a set of Partial Differential Equations where is possible to represent the chemical interactions of the morphogens and the way they move over the space. This kind of dynamics are commonly called reaction-diffusion mechanisms, and the equations that describe them are named Reaction-Diffusion equations. In section [[Team:IPN-UNAM-Mexico/Modeling|modeling]] we formally present them.<br />
<br />
===The Activator-Inhibitor===<br />
<br />
In 1972 A. Gierer and H. Meinhardt published his work called ''A theory of biological pattern formation'' presenting a network based in the interaction of at least two morphogenes acting as an activator and an inhibitor. The main qualitative dynamics of the morphogens is:<br />
<br />
''Short range activation, longer range inhibition and a conceptual distinction between effective concentrations of activator and inhibitor, on one hand, and the density of their sources on the other.''<br />
<br />
Schematically we can see this description as:<br />
<br />
IMAGEN<br />
<br />
<br />
[[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] presented a good example of how patterns can arise from this kind of dynamics so we cite his text literally:<br />
<br />
<center>''Consider a field of dry grass in which there is a large number of grasshoppers''</center><br />
<br />
<center>''which can generate a lot of moisture by sweating if they get warm. Now suppose the''</center><br />
<br />
<center>''grass is set alight at some point and a flame front starts to propagate. We can think of''</center><br />
<br />
<center>''the grasshopper as an inhibitor and the fire as an activator. If there were no moisture''</center><br />
<br />
<center>''to quench the flames the fire would simply spread over the whole field which would''</center><br />
<br />
<center>''result in a uniform charred area. Suppose, however, that when the grasshoppers get''</center><br />
<br />
<center>''warm enough they can generate enough moisture to dampen the grass so that when the''</center><br />
<br />
<center>''flames reach such a pre-moistened area the grass will not burn. The scenario for spatial''</center><br />
<br />
<center>''pattern is then as follows. The fire starts to spread it is one of the reactants, the''</center><br />
<br />
<center>''activator, with a diffusion coefficient DF say. When the grasshoppers, the inhibitor''</center><br />
<br />
<center>''reactant, ahead of the flame front feel it coming they move quickly well ahead of''</center><br />
<br />
<center>''it; that is, they have a diffusion coefficient, DG say, which is much larger than DF .''</center><br />
<br />
<center>''The grasshoppers then sweat profusely and generate enough moisture to prevent the''</center><br />
<br />
<center>''fire spreading into the moistened area. In this way the charred area is restricted to a''</center><br />
<br />
<center>''finite domain which depends on the diffusion coefficients of the reactants fire and''</center><br />
<br />
<center>''grasshopperand various reaction parameters. If, instead of a single initial fire, there''</center><br />
<br />
<center>''were a random scattering of them we can see how this process would result in a final''</center><br />
<br />
<center>''spatially heterogeneous steady state distribution of charred and uncharred regions in''</center><br />
<br />
<center>''the field and a spatial distribution of grasshoppers, since around each fire the above''</center><br />
<br />
<center>''scenario would take place. If the grasshoppers and flame front diffused at the same''</center><br />
<br />
<center>''speed no such spatial pattern could evolve.''</center><br />
<br />
<br />
Synthesizing, we can now represent the interactions between the activator and the inhibitor as follows:<br />
<br />
The activator is autocathalyzed and it also triggers the formation of the inhibitor. Accordingly to its name, the inhibitor inhibits the production of the activator, leading to a simple but very rich dymamics (For more details on the acivator-inhibitor equations please go to [[Team:IPN-UNAM-Mexico/Modeling|modelling]] section). From the grass field and the fire analogy we can deduce that the diffusion coefficients of the fire should be slower than the grasshoppers one; if not the fire (activator) would spread completely in the area. This is an important fact that we mention again later.<br />
<br />
==='''GENERAL CONDITIONS FOR PATTERN GENERATION'''===<br />
<br />
Although this kind of conditions refers mainly to a mathematical analyses of the reaction-diffusion systems like the Activator-Inhibitor of [[Team:IPN-UNAM-Mexico/Modeling/References|J.D. Murray]] , we can qualitative simplify and establish according to this analyses the general conditions for pattern formation:<br />
<br />
<br />
# The existence of at least of two morphogenes with different nature that interacts chemically between them diffuse over the space<br />
# The coefficient rates of diffusion should be different.<br />
# The starting distribution of morphogenes should not be completely homogeneous over the space.<br />
# The Gierer and Mainhardt proposal: local activation and longe range inhibition.<br />
<br />
<br />
==[[Image:Month-icon.png | 50px]]'''TURING MEETS SYNTHETIC BIOLOGY'''==<br />
<br />
The Synthetic Biology has become in the last years an excellent tool to designe biological systems with particular purposes. In our team we decided to used it as a way to contribute not only with technological aspects but mainly with theoretical and foundational research. <br />
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The Turing's ideas about cellular differentiation in zygote according to gradients of morphogenes that react and diffuse through the cellular tissue have not been completely confirmed due to the lack of biological evidence. The main objective of this project is to give an example of a biological system that contains reaction-diffusion mechanisms and is able to reproduce spatiotemporal Turing-type patterns or another kind of nontrivial patterns. <br />
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The biobricks found in the [http://www.partsregistry.org Registry of Biological parts] are a good starting point to construct a synthetic network of genes that due to their interactions could be identified as an Activator-Inhibitor system. This genetic network inserted innto an ''E. coli''' should respond to the concentration gradient of morphogens in the media and have the potential to differentiate accordingly. <br />
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The main challenge was to design a synthetic network that fulfill the general conditions for generating a spatiotemporal pattern (see above). But we must act carefully, since in Murray's book says literaly: <br />
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<center>''"...the genes, however, themselves cannot create the pattern. They only provide a blueprint or recipe, for the pattern generation"''</center> <br />
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an advise that few teams in the past years' competitions may have considered considered.<br />
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==[[Image:Month-icon.png | 50px]]'''Morphogenesis qualitative mechanisms'''==<br />
<center><br />
{| <br />
|[[Image:Curv ACT-INH.jpg |200px|center|texto descriptivo]]<br />
|[[Image:ACT-INH.jpg |200px|center|texto descriptivo]] <br />
|}<br />
</center><br />
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==[[Image:Month-icon.png | 50px]]Reaction-Diffusion systems implemented on Biobricks==<br />
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Inspired by the Gierer and Mainhardt work we designed a synthetic genetic network that acts as an Activator-Inhibitor with limiting substrates. We explain each particular characteristics of reaction, diffusion and substrates in the following subsections.<br />
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===Reaction - Diffusion===<br />
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We suppose the existence of two morphogenes, represented by ''Lux'' and ''Las'' , ''AI'' and ''PAI'' lactones respectively. This substances are very small and travel throw the membrane, and diffuse fast in the media. <br />
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We used two promoters, one inducible by ''LasR''+''PAI'' ([http://www.partsregistry.org/Part:Bba_R0079 Bba_R0079]) and the other double controlled ([http://www.partsregistry.org/Part:Bba_RK091146 Bba_K091146]), repressed by ''LuxR''+''AI ''and induced by ''LasR''+''PAI''<nowiki>; in our genetic network we gave the cell the posibility of responde to a gradient of </nowiki>''PAI'' and ''AI ''and express ''GFP''.<br />
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We used too a constitutive ''Lac'' Inverter, to control the production of ''LasR'' with ''IPTG'', a constitutive ''Tet'' inverter that controls ''LuxR'' with ''ATC. ''These inverters provides a good way to control the systems and make it more sensitive for parameters adjust.<br />
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For a complete documentation of the biobricks check [[Team:IPN-UNAM-Mexico/Parts | parts section]].<br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Lac inverter]]'''====<br />
[[Image:AI Lac.jpg|500px|center|Lac Inverter]]<br />
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The ''Lac ''Inverter is constitutive producing ''LacI ''and repressing ''plac ''promoter. ''Plac ''promoter controls de expression of ''LasR''. <br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Tet inverter]]'''====<br />
[[Image:AI Tet.jpg|500px|center|link=https://2009.igem.org/Team:IPN-UNAM-Mexico/Parts]]<br />
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The Tet'' ''Inverter is constitutive producing ''TetR ''and repressing ''ptet ''promoter. ''Ptet ''promoter controls de expression of ''LuxR''. <br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Lux AHL]]'''====<br />
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[[Image:AI LuxI.jpg|300px|center|Lux AHL]]<br />
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This biobrick is a signaling protein generator that is expected to be activated by ''LasR''+''PAI'' controlling the expression of ''LuxI'' enzyme.<br />
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===='''[[Team:IPN-UNAM-Mexico/Parts | Las AHL]]'''====<br />
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[[Image:AI LasI.jpg|400px|center|Las AHL]]<br />
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This biobrick is a signaling proteing generator that is expected to controlled in two different ways, activated by ''LasR''+''PAI'' and repressed by ''LuxR''+''AI.'' It controls the expression of LasI enzyme and GFP in a polycistronic way.<br />
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===Substrates===<br />
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===='''[http://openwetware.org/wiki/IPTG IPTG] & [http://openwetware.org/wiki/ATc ATC]'''====<br />
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[[Image:AI substrates.jpg|500px|center|substrates]]<br />
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Different concentrations of ''IPTG '' and ''ATC'' is expected to control too the expression of ''LasR'' and ''LuxR'' correspondly<br />
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==[[Image:Month-icon.png | 50px]] The Activator-Inhibitor system on biobricks: The dynamics==<br />
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The questions now is, how the biobricks system works?, this subsection will answer this question starting from a prototypical point of view, the activator activates the inhibitor.<br />
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==='''Autocatalisis'''===<br />
[[Image:AI Biobricks wiki 1.jpg|500px|center|texto descriptivo]]<br />
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First, we idenfify <br />
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==='''Activation'''===<br />
[[Image:AI Biobricks wiki 3.jpg|500px|center|texto descriptivo]]<br />
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==='''Inhibition'''===<br />
[[Image:AI Biobricks wiki 4.jpg|500px|center|texto descriptivo]]<br />
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==='''Diffusion'''===<br />
[[Image:AI Biobricks wiki 5.jpg|500px|center|texto descriptivo]]<br />
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==='''Substrates'''===<br />
[[Image:AI Biobricks wiki 6.jpg|500px|center|texto descriptivo]]<br />
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==='''Complete system'''===<br />
[[Image:AI Biobricks wiki grande.jpg|500px|center|texto descriptivo]]<br />
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{{Template:IPN-UNAM-Mexico-footer}}</div>LUIS DE JESUS